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Terabyte-scale image similarity search: Experience and best practice.

, , , and . BigData, page 674-682. IEEE Computer Society, (2013)

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Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images., , , , , , , , and . ACM Multimedia, page 1029-1031. ACM, (2019)Exquisitor: Interactive Learning at Large., , , , , , , , and . CoRR, (2019)Prototyping a Web-Scale Multimedia Retrieval Service Using Spark., , , and . ACM Trans. Multim. Comput. Commun. Appl., 14 (3s): 65:1-65:24 (2018)Towards Engineering a Web-Scale Multimedia Service: A Case Study Using Spark., , , and . MMSys, page 1-12. ACM, (2017)Terabyte-scale image similarity search: Experience and best practice., , , and . BigData, page 674-682. IEEE Computer Society, (2013)Scalable high-dimensional indexing with Hadoop., , , and . CBMI, page 207-212. IEEE, (2013)Parallelism and distribution for very large scale content-based image retrieval. (Parallélisme et distribution pour des bases d'images à très grande échelle).. University of Rennes 1, France, (2013)Distributed high-dimensional index creation using Hadoop, HDFS and C++., , and . CBMI, page 1-6. IEEE, (2012)Impact of Storage Technology on the Efficiency of Cluster-Based High-Dimensional Index Creation., , and . DASFAA Workshops, volume 7240 of Lecture Notes in Computer Science, page 53-64. Springer, (2012)Indexing and searching 100M images with map-reduce., , , and . ICMR, page 17-24. ACM, (2013)